Simulation of Urban Green Space Landscape and Land Surface Temperature using Land Change Modeler

Abstract

Uncontrolled urban development and uncoordinated master planning are commonplace. Managing green space for climate adaptation may difficult. There is a lack of empirical information in the past and present spatial distribution to predict urban green space and land surface temperature (LST) in an urban city. LST is the most important parameters to study the energy interactions and cycles between the atmosphere and ground surface. LST is governed by surface heat fluxes, which in turn is affected by urbanization. Surface and atmospheric modifications due to urbanization lead to a modified thermal climate that is warmer than the surrounding rural areas, particularly at night. This study aims at predicting the effect of land surface temperature on urban green space landscape in the context of urban expansion. Understanding these phenomena are needed to provide a basis for effective green space planning. Landsat images of 1988, 2002 and 2017 were used to assess the spatiotemporal of landscape changes and land surface temperature in this area. Land Change Model-Markov Chain was used to simulate the effect of urban expansion and urban heat effects on green space landscape. The result shows that the increase of urban expansion and land surface temperature could lower the urban green space and potential loss of the area. The result from this study may provide significant insight into understanding the importance of landscape of green space for cooling the area and provide a healthy environment for dwellers.